Modeling, Verification, and Control of Complex Systems for Energy Networks (Dagstuhl Seminar 14441)

Abstract

Power and energy networks) are systems of great societal and economic relevance and impact, particularly given the recent growing emphasis on environmental issues and on sustainable substitutes (renewables) to traditional energy sources (coal, oil, nuclear). Power networks also represent systems of considerable engineering interest. 

The aim of this Dagstuhl seminar has been to survey existing and explore novel formal frameworks for modeling, analysis and control of complex, large scale cyber-physical systems, with emphasis on applications in power networks. 

Stochastic hybrid systems (SHS) stand for a mathematical framework that allows capturing the complex interactions between continuous dynamics, discrete dynamics, and probabilistic uncertainty. In the context of power networks, stochastic hybrid dynamics arises naturally: (i) continuous dynamics models the evolution of voltages, frequencies, etc.; (ii) discrete dynamics models controller logic and changes in network topology (unit commitment); and (iii) probability models the uncertainty about power demand, power supply from renewables and power market price.

The seminar has covered relevant approaches to modeling and analysis of stochastic hybrid dynamics, in the context of energy networks.